reasoning and chain-of-thought

GLM 5.2 (Reasoning) vs DeepSeek V4 Pro

Both models are live in the Cybrdeck playground. Instead of trusting a single answer or a generic leaderboard, run the same prompt through GLM 5.2 (Reasoning) and DeepSeek V4 Pro side by side and diff the results in the consensus studio — with real latency and credit cost shown per model.

Z.ai

GLM 5.2 (Reasoning)

Z.ai / Zhipu's elite 1M-context reasoning model. Streams `reasoning_content` deltas for the thinking accordion. Massive coding depth at an extremely competitive burn rate.

DeepSeek

DeepSeek V4 Pro

DeepSeek's flagship model with advanced reasoning and multi-lingual capabilities.

Spec comparison

Z.aiProviderDeepSeek
1.0M tokensContext164K tokens
standardTierpremium
1.4Credits / 1k in0.435
4.4Credits / 1k out0.87
YesReasoning controlYes
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Which costs less on Cybrdeck?

GLM 5.2 (Reasoning) burns 4.4 credits per 1,000 output tokens; DeepSeek V4 Pro burns 0.87. DeepSeek V4 Pro is the lower-cost option for the same output volume. Credit rates are Cybrdeck's published playground multipliers, so the numbers move with the catalog rather than a snapshot.

Frequently asked

What is the difference between GLM 5.2 (Reasoning) and DeepSeek V4 Pro?+

GLM 5.2 (Reasoning) is served by Z.ai with a 1.0M-token context window; DeepSeek V4 Pro comes from DeepSeek with 164K tokens. In Cybrdeck you run both on the same prompt and diff the answers side by side instead of trusting a single model's take.

Which is cheaper to run, GLM 5.2 (Reasoning) or DeepSeek V4 Pro?+

On Cybrdeck credits, GLM 5.2 (Reasoning) burns 4.4 credits per 1,000 output tokens and DeepSeek V4 Pro burns 0.87. DeepSeek V4 Pro is the lower-cost option for the same output volume.

Can I use GLM 5.2 (Reasoning) and DeepSeek V4 Pro side by side?+

Yes. The Cybrdeck playground runs multiple models on one prompt in a consensus studio, so you see exactly where GLM 5.2 (Reasoning) and DeepSeek V4 Pro agree and where they diverge — starting on the free tier.

Which model should I pick for reasoning and chain-of-thought?+

It depends on your workload. Run both against your own prompt in the playground: Cybrdeck shows latency and credit cost per model, so you decide from your real task rather than a generic leaderboard.

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